Recent advancements in gene editing technologies have significantly enhanced the precision and efficiency of genetic modifications, particularly through innovative delivery systems and editing tools. One notable development is the engineered nucleocytosolic vehicles that utilize virus-like particles (VLPs) for the safe and efficient delivery of programmable editors. This system allows for the preferential loading of fully assembled ribonucleoproteins (RNPs), thereby improving the efficacy of various editing techniques such as prime editing and base editing across multiple cell types (ref: Geilenkeuser doi.org/10.1016/j.cell.2025.03.015/). Additionally, the introduction of the Variant-EFFECTS method has enabled researchers to systematically dissect and reprogram gene expression by introducing hundreds of designed edits to regulatory DNA, providing a deeper understanding of transcription factor binding and its implications for cell-type-specific gene expression (ref: Martyn doi.org/10.1016/j.cell.2025.03.034/). Furthermore, the development of QBEmax, a highly efficient cytosine base editor, demonstrates significant improvements in product purity and reduced off-target effects, achieving an impressive 99.8% of edits being C-to-T conversions (ref: Hu doi.org/10.1038/s41587-025-02641-9/). These advancements underscore the potential of gene editing technologies to revolutionize therapeutic strategies in various fields, including regenerative medicine and cancer treatment. Moreover, the exploration of RNA base editing has also gained traction, with studies revealing improved methodologies that mimic highly edited endogenous ADAR substrates, enhancing the safety and specificity of RNA editing applications (ref: Sun doi.org/10.1038/s41587-025-02628-6/). The introduction of high-resolution imaging techniques, such as Oligo-LiveFISH, has further facilitated the study of chromatin dynamics, linking genome organization to cellular processes and disease states (ref: Zhu doi.org/10.1016/j.cell.2025.03.032/). Lastly, the TRADE statistical model has been proposed to improve the analysis of differential expression in perturbation atlases, addressing the challenges posed by noise in single-cell CRISPR screens and enhancing the reliability of transcriptomic profiling (ref: Nadig doi.org/10.1038/s41588-025-02169-3/). Collectively, these studies highlight the rapid evolution of gene editing technologies and their transformative potential in biomedical research.